Zobrazeno 1 - 10
of 1 191
pro vyhledávání: '"Usynin IF"'
Fine-tuning large language models (LLMs) for specific tasks introduces privacy risks, as models may inadvertently memorise and leak sensitive training data. While Differential Privacy (DP) offers a solution to mitigate these risks, it introduces sign
Externí odkaz:
http://arxiv.org/abs/2411.15831
Backdoor attacks compromise the integrity and reliability of machine learning models by embedding a hidden trigger during the training process, which can later be activated to cause unintended misbehavior. We propose a novel backdoor mitigation appro
Externí odkaz:
http://arxiv.org/abs/2407.07662
Often we consider machine learning models or statistical analysis methods which we endeavour to alter, by introducing a randomized mechanism, to make the model conform to a differential privacy constraint. However, certain models can often be implici
Externí odkaz:
http://arxiv.org/abs/2405.13677
Quantifying the impact of individual data samples on machine learning models is an open research problem. This is particularly relevant when complex and high-dimensional relationships have to be learned from a limited sample of the data generating di
Externí odkaz:
http://arxiv.org/abs/2311.03075
Obtaining high-quality data for collaborative training of machine learning models can be a challenging task due to A) regulatory concerns and B) a lack of data owner incentives to participate. The first issue can be addressed through the combination
Externí odkaz:
http://arxiv.org/abs/2305.02942
Autor:
Evgeny L. Choynzonov, Alexander A. Fedenko, Natalia A. Falaleeva, Tatiana V. Andreeva, Sergei G. Afanas'ev, Zelimkhan A. Bakaev, Danila I. Valiev, Aleksandr A. Volkov, Larisa A. Kolomiets, Tatiana V. Krashikhina, Sergei V. Miller, Viktoriia V. Mikhaliuk, Andrei N. Ogloblin, Svetlana A. Orlova, Stanislav V. Pataliak, Ilya A. Pokataev, Nataliia O. Popova, Olesia V. Rebrina, Rustem N. Safin, Irina Iu. Stradaeva, Iuliia V. Trefilova, Inessa S. Usol'tseva, Evgenii A. Usynin, Sergey V. Sharov, Denis Iu. Iukal'chuk, Aishat R. Iasieva
Publikováno v:
Современная онкология, Vol 26, Iss 2, Pp 173-181 (2024)
Background. Post-registration observational studies with switching therapy from the original drug to a biosimilar for non-medical indications allow us to assess the safety and effectiveness of this type of switching in real clinical practice. Aim.
Externí odkaz:
https://doaj.org/article/d14ddd461b434759b7f775f2404d2a49
Membership inference attacks aim to infer whether a data record has been used to train a target model by observing its predictions. In sensitive domains such as healthcare, this can constitute a severe privacy violation. In this work we attempt to ad
Externí odkaz:
http://arxiv.org/abs/2212.01082
Autor:
Mueller, Tamara T., Kolek, Stefan, Jungmann, Friederike, Ziller, Alexander, Usynin, Dmitrii, Knolle, Moritz, Rueckert, Daniel, Kaissis, Georgios
Differential privacy (DP) is typically formulated as a worst-case privacy guarantee over all individuals in a database. More recently, extensions to individual subjects or their attributes, have been introduced. Under the individual/per-instance DP i
Externí odkaz:
http://arxiv.org/abs/2211.10173
In federated learning for medical image analysis, the safety of the learning protocol is paramount. Such settings can often be compromised by adversaries that target either the private data used by the federation or the integrity of the model itself.
Externí odkaz:
http://arxiv.org/abs/2205.02652
Autor:
Maria I. Volkova, Alexey S. Kalpinskiy, Olesya A. Goncharova, Konstantin V. Menshikov, Elena V. Karabina, Aleksand S. Dergunov, Natalya I. Polshina, Elena N. Alexandrova, Andrey A. Lebedinets, Alexey К. Panov, Alexander V. Sultanbaev, Evgeny A. Usynin, Mikhail V. Volkonskiy, Viktorya V. Mikhalyuk, Ruslan A. Zukov, Yulia V. Anzhiganova, Magomed A. Gusniev, Elena N. Igumnova, Svetlana V. Kuzmicheva, Ilya A. Pokataev, Anna S. Olshanskaya, Natalia I. Pervakova, Elvira L. Parsadanova, Tatyana A. Sannikova, Alexandr A. Bystrov, Daria M. Dubovichenko, Mukhitova R. Miliausha, Viacheslav A. Chubenko, Konstantin A. Shkret, Mariya N. Gorshenina, Mavzhuda К. Davlatova, Alina E. Kosareva, Olga A. Lutoshkina, Oxana A. Maslova, Maria V. Makhnutina, Anna V. Mishina, Makhabbat Zh. Murzalina, Oksana A. Podyacheva, Sergey A. Kalinin, Ovsep A. Mailyan, Alfiya R. Safarova, Ksenia O. Semenova, Mariya A. Strokova, Ekaterina Yu. Urashkina, Olesya S. Shmygina
Publikováno v:
Современная онкология, Vol 26, Iss 1, Pp 39-47 (2024)
Aim To evaluate the safety and toxicity of lenvatinib with pembrolizumab in unselected patients with advanced renal cell carcinoma (RCC). Materials and methods. The Russian phase IV observational study included 151 patients with advanced RCC who r
Externí odkaz:
https://doaj.org/article/b8f04fb084054d4fa93d3b87907a155b